Welcome To

BRAin INtelligence and Machine Learning (BRAINML) @ Georgia Tech

The lab focuses on developing probabilistic modeling approaches and scalable and efficient inference algorithms, with applications to neural and behavior analyses, as well as many real-world problems.

More specifically, the modeling topics involve: deep generative models, variational autoencoder, (deep) Gaussian process, Bayesian (convolutional) neural net, Bayesian nonparametric, Bayesian optimization and active learning, computer vision, hierarchical spatial and temporal models, latent dynamic models, (inverse) reinforcement learning, etc.

The applications cover but are not limited to: neural latent discovery, 3D full-body kinematic model estimation, identifying behavior syllables, studying intrinsic motives and reward representations of animal and human behaviors, fMRI decoding, neural sensory encoding, optimal experimental design, etc.